Sistema embarcado baseado em lógica fuzzy para análise da qualidade do ar em ambientes internos

Abstract

The growing concern about indoor air quality has driven the development of smart solutions for its monitoring and control. This dissertation presents a fuzzy logic-based system for evaluating environmental comfort in classrooms, considering environmental variables such as humidity, tem perature, carbon monoxide (CO), and carbon dioxide (CO2). Data for these variables are acquired by sensors connected to an embedded platform. The fuzzy system’s output is a variable called “Comfort”, inspired by the principles of the Air Quality Index (AQI), used to activate a humidifier via a servomotor, automatically adjusting humidity levels proportionally to ambient conditions. The system was implemented using Arduino for physical control and Python for real-time data processing, and its performance was compared to that of a traditional proportional-integral derivative (PID) controller. The results showed that, in comparison with the PID controller, the fuzzy approach exhibited lower variability in response to changes in the indoor environment, performing smoother and more consistent adjustments in humidity control. This behavior led to improved overall performance and greater energy efficiency. These findings highlight the potential of fuzzy logic as an effective and reliable alternative for continuous indoor air quality monitoring applications.